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When you want to manage projects across your businesses using a kanban + Eisenhower methodology. One kanban per business (whatever portfolio of businesses, projects, or initiatives you run). Tool-agnostic — connects via API/MCP to whatever PM tool each business uses (Notion, GitHub Projects, Plane, Linear, Obsidian file-based, or manual mode). Async-first output. Six modes — setup (scaffold a new board for a business), triage (Eisenhower-sort the backlog), next (pick the next thing to work on, single board or across all), status (paste-ready async snapshot), unblock (diagnose Review/Blocked column), weekly (Friday pulse + week planning). Triggers on "/pm," "/pm setup," "/pm triage," "/pm next," "/pm status," "/pm unblock," "/pm weekly," "what should I work on next," "kanban status," "Eisenhower this," "triage my backlog," "what's blocked."

日本語の概要は準備中です。原文の説明を表示しています。

Navigation skill for genre project scaffolds: pick platformer/RPG/FPS (or other genre) then load matching template scripts and route gameplay fill to godot-genre-* skills. Use when bootstrapping architecture, bootstrap order, pause modes, PCK DLC, or feature tags — not for pasting FPS/inventory recipes. Keywords: project templates, bootstrap, Subsystem Locator, PCK, feature tags, PROCESS_MODE_ALWAYS, genre scaffold.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for AnimationPlayer including track types (Value, Method, Audio, Bezier), root motion extraction, animation callbacks, procedural animation generation, call mode optimization, and RESET tracks. Use for timeline-based animations, cutscenes, or UI transitions. Trigger keywords: AnimationPlayer, Animation, track_insert_key, root_motion, animation_finished, RESET_track, call_mode, animation_set_next, queue, blend_times.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.

日本語の概要は準備中です。原文の説明を表示しています。

Bevy ECS skill for desktop windows. Use when setting the primary window size, present mode, fullscreen, or close behavior. Keywords: Bevy, window, desktop, WindowPlugin, PrimaryWindow, WindowMode.

日本語の概要は準備中です。原文の説明を表示しています。

Navigation skill for genre project scaffolds: pick platformer/RPG/FPS (or other genre) then load matching template scripts and route gameplay fill to godot-genre-* skills. Use when bootstrapping architecture, bootstrap order, pause modes, PCK DLC, or feature tags — not for pasting FPS/inventory recipes. Keywords: project templates, bootstrap, Subsystem Locator, PCK, feature tags, PROCESS_MODE_ALWAYS, genre scaffold.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for AnimationPlayer including track types (Value, Method, Audio, Bezier), root motion extraction, animation callbacks, procedural animation generation, call mode optimization, and RESET tracks. Use for timeline-based animations, cutscenes, or UI transitions. Trigger keywords: AnimationPlayer, Animation, track_insert_key, root_motion, animation_finished, RESET_track, call_mode, animation_set_next, queue, blend_times.

日本語の概要は準備中です。原文の説明を表示しています。

Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is enabled) triggering deployments with human confirmation. Use when the user wants to: (1) Set up the Temps MCP server, (2) Connect Claude Code/Desktop, Codex, Cursor, VS Code, Windsurf, or Zed to Temps, (3) Add Temps tools to an AI assistant, (4) Test the MCP wizard locally, (5) Manage multiple Temps MCP connections (dev, staging, prod, or several local dev slots) side by side. Triggers: "temps mcp", "configure temps tools", "add temps to claude", "temps ai assistant", "mcp server setup", "mcp add", "test the mcp wizard".

日本語の概要は準備中です。原文の説明を表示しています。

DCF valuation model for A-share stocks using Chinese financial data. Uses AkShare MCP for financial statements, WACC inputs (risk-free rate from China government bond yields), and growth projections. Use instead of the original dcf-model skill for Chinese equities.

日本語の概要は準備中です。原文の説明を表示しています。

Roll forward A-share financial models for new periods. Adapts the original roll-forward skill for Chinese financial statements, CAS conventions, and A-share reporting calendars. Triggers on "A股模型滚动", "模型更新", "roll forward model China", "roll forward", "更新财务模型", or "project [company] [period]".

日本語の概要は準備中です。原文の説明を表示しています。

Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.

日本語の概要は準備中です。原文の説明を表示しています。

Design or redesign frontend UI, presentations, and graphics on the Superdesign canvas with a choice of leading AI models. Use whenever the user wants to design a page, feature, flow, slide deck, or brand-new product; improve or reproduce existing UI; compare design results across top models; explore visual variants; set or extract a design system; build reusable components or multi-page flows; create presentations; or create posters and marketing graphics, even if they never say the word 'design tool'. Also supports generating supporting image or video assets when a design needs them.

日本語の概要は準備中です。原文の説明を表示しています。

Build Lightricks LTX-2 / LTX-2.3 video workflows covering text-to-video, image-to-video, GGUF and bundled checkpoints, distilled model, camera control LoRAs, synchronized audio, two-stage upscaling, and swapping alternate/GGUF base models

日本語の概要は準備中です。原文の説明を表示しています。

Discover Civitai models with the BUILT-IN download_model action:"search_civitai" and install/generate them locally. Find a checkpoint/LoRA/embedding on Civitai, download it into ComfyUI, and use its trigger words. Optionally pair the official Civitai MCP for community features (images browsing, posting, collections).

日本語の概要は準備中です。原文の説明を表示しています。

Pick the right ComfyUI startup flags for VRAM, attention, caching, and speed. The full decision matrix for OOM (--novram / --cache-none / --disable-smart-memory), shared-VRAM creep on Windows (--reserve-vram N), model-switching with big text encoders (--cache-none), high-VRAM throughput (--gpu-only / --highvram), and attention-backend selection (--use-sage-attention for speed, --use-pytorch-cross-attention as the highest-quality / Z-Image-safe fallback). Also the acceleration-stack + Blackwell/RTX 5000 (sm_120) notes. Use when a graph OOMs (especially long video like LTX 2 / WAN), when the GPU spills into shared VRAM and slows to a crawl, when switching between models eats all RAM, when Z-Image produces black/garbled output under Sage, or when deciding which attention backend to launch with. Flag names verified against upstream comfy/cli_args.py; see Sources.

日本語の概要は準備中です。原文の説明を表示しています。

Upscale and restore video in ComfyUI. Both the quick local path (per-frame ESRGAN like 4x_foolhardy_Remacri via ImageUpscaleWithModel + 4x→2x supersample, with its temporal-flicker tradeoff) and temporal-aware super-resolution (SeedVR2, the newer FlashVSR) with the downscale-first restore pipeline; RIFE/FILM frame interpolation via the BUILT-IN ComfyUI 0.26 FrameInterpolate (rife_v4.26 in models/frame_interpolation/) or the ComfyUI-Frame-Interpolation pack; 2x/4x scaling, VRAM tiers, VHS encode. Captures the classic downscale→SeedVR2→RIFE recipe and the current 2026 recommendation.

日本語の概要は準備中です。原文の説明を表示しています。

Run the ComfyUI agent locally for FREE with no subscription, no API key, and fully offline, using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama. Use when the user asks about running locally, running for free, offline use, avoiding API costs, Ollama setup, or which local model to pick.

日本語の概要は準備中です。原文の説明を表示しています。

Extend / continue a video temporally with Pusa 2.2 in ComfyUI. Temporal flowmatching (the flowmatch_pusa scheduler + WanVideoAddPusaNoise) on the WanVideoWrapper stack with WAN 2.2 T2V A14B (HIGH/LOW) models and the Pusa V1 LoRAs, conditioning on the loaded clip via WanVideoEncode so the existing motion carries into the continuation. Covers the kijai wanvideo_2_2_14B_Pusa_extension graph, model/LoRA slots + downloads, noise/length/scheduler settings, chaining multiple extensions, VRAM tiers, gotchas, and the extend→upscale handoff.

日本語の概要は準備中です。原文の説明を表示しています。

CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.

日本語の概要は準備中です。原文の説明を表示しています。

SwiftData class inheritance patterns for hierarchical models with type-based querying, polymorphic relationships, and when to choose inheritance vs enums. Use when designing SwiftData model hierarchies.

日本語の概要は準備中です。原文の説明を表示しています。

On-device LLM integration using Apple's Foundation Models framework. Use when implementing AI text generation, structured output, or tool calling.

日本語の概要は準備中です。原文の説明を表示しています。

SwiftData skills — class inheritance patterns for hierarchical models, type-based querying, polymorphic relationships, and inheritance-vs-enum decisions. Use when designing SwiftData model hierarchies.

日本語の概要は準備中です。原文の説明を表示しています。

导演并制作多类型视频，从创意、研究、剧本、视觉开发、人物与声音设计、分镜和生成 Prompt，一直推进到素材生成、任务追踪与交付。适用于 Storytime Animation、Animated Explainer 与 Cinematic Drama，三个 Mode 均已完成实际作品验证。尚未建立专属 Mode 的类型不得冒充已支持流程。

日本語の概要は準備中です。原文の説明を表示しています。